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Smart data capture (SDC), also known as 'intelligent data capture' or 'automated data capture', describes the branch of technology concerned with using computer vision techniques like optical character recognition (OCR), barcode scanning, object recognition and other similar technologies to extract and process information from semi-structured and unstructured data sources. IDC characterize smart data capture as an integrated hardware, software, and connectivity strategy to help organizations enable the capture of data in an efficient, repeatable, scalable, and future-proof way.[1] Data is captured visually from barcodes, text, IDs and other objects - often from many sources simultaneously - before being converted and prepared for digital use, typically by artificial intelligence-powered software.[2] An important feature of SDC is that it focuses not just on capturing data more efficiently but serving up easy-to-access, actionable insights at the instant of data collection to both frontline and desk-based workers, aiding decision-making and making it a two-way process.

Smart data capture automates and accelerates capture, applying insights in real time and automating processes based on extracted input. Smart data capture is designed to be repeatable and scalable to reduce low-level manual tasks and eliminate human error. To achieve this goal, smart data capture solutions are often made available using specialist software installed on commodity hardware such as smartphones.[3] However, some solutions may rely on specialized hardware such as dedicated scanning devices, wearables[4] or shop floor robots.[5]

Differences from OCR

Optical character recognition applications are typically concerned with the actual data capture process; they are intended to faithfully reproduce text, words, letters and symbols from a printed document. Smart data capture is multimodal,[6] capable of extracting data from a wider range of semi-structured and unstructured sources, going beyond basic text recognition to offer a wider scope of applications. By extending functionality to provide actionable insights at the point of capture, SDC is also a two-way process (capture-display), while OCR is more commonly one-way (capture only), primarily used for data input.[7]

Smart data capture solutions typically have two parts:

  • Data capture (which includes OCR, barcode scanning, object recognition)
  • Functionality that then uses this data to provide actionable insights at the point of capture.

Applications

Smart data capture can be applied to almost any industry and application that requires visual information capture and interpretation. This may include:

  • Retail[8]
  • Warehouse inventory control
  • Logistics, handling and shipping[9]
  • Manufacturing
  • Field service
  • Healthcare[10]
  • Transport and travel[11]
  • Fraud detection
  • Immersive, augmented reality-driven experiences[12]

Notable Smart Data Capture Vendors

Notes

Historically, PriceWaterhouseCoopers described smart data capture as a combination of robotic process automation and intelligent character recognition.[13] This description is no longer sufficient because it is focused purely on text-based capture systems (automated OCR).

See also

References

  1. ^ Arcaro, Matt (January 2023). Smart Data Capture: A Technology Strategy to Scale Data Intelligence (PDF). IDC (Report).
  2. ^ Mueller, Samuel (17 November 2022). "What Companies Should Know About Smart Data Capture And Last-Mile Delivery". Forbes Technology Council.
  3. ^ "How smart data capture solutions on Samsung Galaxy rugged devices are helping transform business operations". Samsung. 27 October 2022.
  4. ^ Bauer, Dennis; Wutzke, Rolf; Bauernhansl, Thomas (2016). "Wear@Work – A New Approach for Data Acquisition Using Wearables". Procedia Cirp. 50: 529–534. doi:10.1016/j.procir.2016.04.121. S2CID 114410108.
  5. ^ Anstee, James (14 January 2022). "Scandit launches smart shelf management for retailers". Electronic Specifier.
  6. ^ "9 Principles of a Smart Data Capture Strategy". iCrunchData. 8 June 2023.
  7. ^ BasuMallick, Chiradeep (30 January 2023). "What Is OCR (Optical Character Recognition)? Meaning, Working, and Software". Spiceworks.
  8. ^ Pressley, Alix (19 January 2023). "Smart data capture unlocks uplifted employee and customer experience". Intelligent CIO.
  9. ^ "Why is Mobile Data Capture Important for Transport Logistic Firms". Dynamsoft. 28 December 2022.
  10. ^ Flannery, Ellen (13 March 2023). "The nurse's journey: how smart data capture will revolutionise hospital processes". Intelligent Health.tech.
  11. ^ "SAS (Scandinavian Airlines) Improves Customer Service and Cuts Costs with Scandit's Barcode Scanning on Smartphones". Business Wire. 9 December 2019.
  12. ^ Vala, Melanie (24 January 2023). "Why the Mobile Experience Is Important for E-Commerce". AIthority.
  13. ^ Kamra, Nitin (2018). Robotic process automation and intelligent character recognition: Smart data capture (PDF). PriceWaterhouseCooper (Report).
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